SIAM Journal on Computing
Parameter-controlled volume thinning
CVGIP: Graphical Models and Image Processing
Skeletonization of Three-Dimensional Object Using Generalized Potential Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A new shape descriptor for surfaces in 3D images
Pattern Recognition Letters
Introduction to Algorithms
International Journal of Computer Vision
Characterization and Recognition of 3D Organ Shape in Medical Image Analysis Using Skeletonization
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
A Topological Approach for Segmenting Human Body Shape
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
A Survey of Content Based 3D Shape Retrieval Methods
SMI '04 Proceedings of the Shape Modeling International 2004
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Automatic Segmentation of Scanned Human Body Using Curve Skeleton Analysis
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Heat diffusion approach for feature-based body scans analysis
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
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This paper describes an approach for constructing a graph representation of 3D objects and more particularly of articulated and tubular-like objects. For objects without cavities, this representation is a tree structure that encodes the object template while being invariant to global and local rigid transformation. The approach described in this paper has some interesting aspects: (1) It operates on raw 3D scattered data points, without any pre-processing stage. (2) It has low computational cost. (3) It is robust against irregular data point distribution and data deficiencies. This graph representation can be used in various applications such as object coding, recognition, and segmentation.